---
base_model: aubmindlab/bert-base-arabertv02
tags:
- generated_from_trainer
model-index:
- name: arabert_cross_vocabulary_task4_fold3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# arabert_cross_vocabulary_task4_fold3

This model is a fine-tuned version of [aubmindlab/bert-base-arabertv02](https://huggingface.co/aubmindlab/bert-base-arabertv02) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9487
- Qwk: 0.7917
- Mse: 0.9487

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Qwk    | Mse    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| No log        | 0.0308 | 2    | 2.5656          | 0.1026 | 2.5656 |
| No log        | 0.0615 | 4    | 1.5800          | 0.2273 | 1.5800 |
| No log        | 0.0923 | 6    | 1.4668          | 0.3238 | 1.4668 |
| No log        | 0.1231 | 8    | 1.7439          | 0.5345 | 1.7439 |
| No log        | 0.1538 | 10   | 1.8731          | 0.5182 | 1.8731 |
| No log        | 0.1846 | 12   | 1.6136          | 0.5153 | 1.6136 |
| No log        | 0.2154 | 14   | 1.0770          | 0.6447 | 1.0770 |
| No log        | 0.2462 | 16   | 0.8334          | 0.6452 | 0.8334 |
| No log        | 0.2769 | 18   | 0.8987          | 0.6213 | 0.8987 |
| No log        | 0.3077 | 20   | 1.0528          | 0.6192 | 1.0528 |
| No log        | 0.3385 | 22   | 1.1536          | 0.6127 | 1.1536 |
| No log        | 0.3692 | 24   | 1.1237          | 0.6677 | 1.1237 |
| No log        | 0.4    | 26   | 1.0225          | 0.7612 | 1.0225 |
| No log        | 0.4308 | 28   | 0.9282          | 0.7931 | 0.9282 |
| No log        | 0.4615 | 30   | 0.8550          | 0.7997 | 0.8550 |
| No log        | 0.4923 | 32   | 0.8655          | 0.8051 | 0.8655 |
| No log        | 0.5231 | 34   | 0.8784          | 0.7955 | 0.8784 |
| No log        | 0.5538 | 36   | 0.9842          | 0.7843 | 0.9842 |
| No log        | 0.5846 | 38   | 0.9740          | 0.7860 | 0.9740 |
| No log        | 0.6154 | 40   | 0.9578          | 0.7855 | 0.9578 |
| No log        | 0.6462 | 42   | 0.8675          | 0.7868 | 0.8675 |
| No log        | 0.6769 | 44   | 0.8691          | 0.7893 | 0.8691 |
| No log        | 0.7077 | 46   | 0.9121          | 0.7886 | 0.9121 |
| No log        | 0.7385 | 48   | 0.9594          | 0.7961 | 0.9594 |
| No log        | 0.7692 | 50   | 0.9137          | 0.7879 | 0.9137 |
| No log        | 0.8    | 52   | 0.8811          | 0.7869 | 0.8811 |
| No log        | 0.8308 | 54   | 0.8791          | 0.7869 | 0.8791 |
| No log        | 0.8615 | 56   | 0.9161          | 0.7964 | 0.9161 |
| No log        | 0.8923 | 58   | 0.9349          | 0.7936 | 0.9349 |
| No log        | 0.9231 | 60   | 0.9520          | 0.7971 | 0.9520 |
| No log        | 0.9538 | 62   | 0.9575          | 0.7917 | 0.9575 |
| No log        | 0.9846 | 64   | 0.9487          | 0.7917 | 0.9487 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1